I spent a decent chunk of today working on the fitness function for Distributed Neuron, as well as general housekeeping. The fitness function is very simple at the moment. It tallies the lifetime of the organism and the total distance moved then normalizes these based on the predefined weights. This is performed for each trial. At the end of all the trials, the delta is computed. Delta is the average change from one trial to the next. If an organism slowly improves its fitness as trials progress, the delta value at the end will reflect this. The delta score and raw score are then normalized using predefined weights and the final fitness for the genotype is recorded.

Some work was done on the structure and flow controls leading to a fully autonomous client. It can start and stop at any time during trials and recover with minimal loss of data. It also can complete full life cycles, evolving one genotype after the next.

The next step is to build a small, random starting genetic population and start coding crossover mutation. Current genotypes are directly mutated from the parent. Crossover will bring in selective sexual pressure which will move the project much better than random mutation alone. I’m excited, I’ll be able to start running the client full time. Real data gathering can start in earnest soon!